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arXiv · 1804.01365

Bayesian model selection with fractional Brownian motion

Jens Krog·Lars H. Jacobsen·Frederik W. Lund·Daniel Wüstner·Michael A. Lomholt
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Abstract

We implement Bayesian model selection and parameter estimation for the case of fractional Brownian motion with measurement noise and a constant drift. The approach is tested on artificial trajectories and shown to make estimates that match well with the underlying true parameters, while for model selection the approach has a preference for simple models when the trajectories are finite. The approach is applied to observed trajectories of vesicles diffusing in Chinese hamster ovary cells. Here it is supplemented with a goodness-of-fit test, which is able to reveal statistical discrepancies between the observed trajectories and model predictions.

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BibTeXRIS

Jens Krog, Lars H. Jacobsen, Frederik W. Lund, Daniel Wüstner, Michael A. Lomholt. 2018-04-04. Bayesian model selection with fractional Brownian motion. https://arxiv.org/abs/1804.01365

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